Computational Investing, Part I

Computational Investing, Part I

Georgia Institute of Technology

About this course: Why do the prices of some companies’ stocks seem to move up and down together while others move separately? What does portfolio “diversification” really mean and how important is it? What should the price of a stock be? How can we discover and exploit the relationships between equity prices automatically? We’ll examine these questions, and others, from a computational point of view. You will learn many of the principles and algorithms that hedge funds and investment professionals use to maximize return and reduce risk in equity portfolios.

In this module, you will understand the course content from a portfolio manager's viewpoint, the incentives for portfolio managers, types of hedge fund, and how to assess fund performance; Also, you will gain insight into market orders, the basic infrastructure of an exchange, and computational components of a hedge fund.

In this module, you will learn how to value a company, and an overview of the theory Capital Assets Pricing Model (CAPM), its assumptions, implications and how you can apply it in fund management. Finally, you will learn to install QSTK Software.

In this module, you will learn about information may affect equity prices and company value, understand efficient market hypothesis and how event studies work; Also, you will learn about the inputs and outputs of a portfolio optimizer, correlation and covariance, Mean Variance Optimization, and the Efficient Frontier.

We will go into more detail in this module about how to read an event study. We will also talk about the differences between actual and adjusted
historical price data, and how to detect and fix wrong data.

In this module, you will learn the fundamental law of active portfolio management. We will recap CAPM, and extend it for portfolios. Finally, we're going to look at ways that we can leverage the capital assets
pricing model to manage, maybe even reduce market risk.

In this module, we will dive deeper into a few examples of information feeds, and learn about technical analysis, and look at a few example technical indicators. Finally, we are going to learn about Bollinger Bands.

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

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Georgia Institute of Technology

The Georgia Institute of Technology is one of the nation's top research universities, distinguished by its commitment to improving the human condition through advanced science and technology.
Georgia Tech's campus occupies 400 acres in the heart of the city of Atlanta, where more than 20,000 undergraduate and graduate students receive a focused, technologically based education.

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Ratings and Reviews

Rated 4.5 out of 5 of 508 ratings

Very nice opportunity to learn about quantitative approach investing. This course has opened to me a new door of interest. Thanks professor Tuker Balch and GT team for the initiative in share that subject and not less important, thanks coursera and coursera team in giving us the opportunity (and turn this opportunity democratic and accessible to who wants improve career) in get learning with one of the best universities abroad.

is

The library QSTK is old and have fails with pandas an numpy.

MS

Loved the course, but wish that the content had more depth. That said, I wish there was a follow-up course to this one (Part II, maybe?) that provided greater insights into the real-world complexity of managing a fund/portfolio. All in all, I'd definitely recommend this course to anyone that's just getting started in the field.